🧪 Macromolecule–Ligand Binding — Full Summary (All Pages)

📄 Page 1 — Recap of core concepts

This lecture builds on:

• Binding stoichiometry (N): number of ligand binding sites per macromolecule
• Dissociation constant (KD): affinity measure
• Thermodynamics: ΔG, ΔH, ΔS
• Cooperativity: sites influencing each other
• Data plots: different ways to extract KD

👉 Big picture: everything in this lecture is about quantifying how strongly ligands bind and how to measure it experimentally.

📄 Page 2 — What does KD mean?

• KD range: 10⁻² to 10⁻¹⁵ M
  • High KD → weak binding
  • Low KD → strong binding

🧠 Key insight:

• In cells, KD is evolutionarily tuned
• Typically:
  • You never have 100% binding
  • You have a mixture of:
    • free ligand
    • free macromolecule
    • complex

👉 This balance is crucial for regulation.

📄 Page 3 — Dissociation math

Reaction: ML ightleftharpoons M + L

Leads to a quadratic equation:

• Because both M and L change during dissociation

👉 Important:

• You cannot always assume L = constant
• Must solve properly when concentrations are similar

📄 Page 4 — KD controls dissociation

Table shows:

👉 Interpretation:

• Lower KD = tighter binding = less dissociation
• Even at same concentrations, affinity dominates behavior

📄 Page 5 — L vs Ltot ⚠️ (Important concept)

Left figure (enzyme kinetics):

• Usually: S approx S_ because enzyme is low

Right figure (binding):

• Not true: L < L_

🧠 Why?

• Ligand binds significantly → reduces free ligand

👉 Critical takeaway:

• In binding experiments, you must account for ligand depletion

📄 Page 6 — Full binding equation

When using Ltot instead of L, you get a more complex equation.

👉 Concept:

• Mass conservation:
  • (M = M_ - ML)
  • (L = L_ - ML)

⚠️ This is why:

• Binding curves are nonlinear
• Requires fitting models

📄 Page 7 — Saturation curves (figure explanation)

Graph shows:

• % saturation vs ligand added
• Different KD values

Key observations:

• Lower KD → curve shifts left (binds earlier)
• At Ltot/Mtot = 1, saturation ~50% depends on KD

👉 Important conclusion:

• You can determine KD even using only total ligand

📄 Page 8–10 — Microscopic KD

What is it?

• KD for individual binding sites

Example:

• Site I and II have different affinities

👉 Problem:

• Hard to measure directly because:
  • signals usually reflect average binding

📄 Page 11 — Macroscopic KD

• What experiments usually measure

👉 Definition:

• Average binding behavior across all sites

🧠 Summary:

📄 Page 12 — Cooperativity (core concept)

Definitions:

• Positive cooperativity: binding increases affinity of next site
• Negative cooperativity: binding decreases affinity

📊 Figure:

• Sigmoidal curve = positive cooperativity
• Hyperbolic = no cooperativity

📄 Page 13 — Why cooperativity matters

• Sharp transition between:
  • low binding → high binding

👉 Acts like a molecular switch

Example:

• Hemoglobin oxygen binding

📄 Page 14 — Two non-cooperative sites (figure)

Graph shows:

• Three populations:
  • no ligand
  • one ligand
  • two ligands

🧠 Insight:

• Intermediate state (1 ligand) is significant

📄 Page 15 — Cooperative sites

• Intermediate state is reduced

👉 Meaning:

• Binding happens more “all-or-none”

📄 Page 16 — Hemoglobin example

Figure shows:

• Cooperative binding increases oxygen delivery

👉 Key takeaway:

• Cooperativity improves biological efficiency

📄 Page 17 — Methods to measure binding

Two categories:

1. No separation (direct signal)

• Fluorescence
• CD
• NMR
• ITC

2. Separation methods

• Dialysis
• Chromatography

👉 Signal: heta = ext{fractional saturation}

📄 Page 18 — Equilibrium dialysis

Principle:

• Semi-permeable membrane:
  • ligand passes
  • protein does not

👉 At equilibrium:

• free ligand equal on both sides

🧠 Use:

• Measure binding indirectly

📄 Page 19 — Gel chromatography

Figure explanation:

• Protein + ligand → peak shift
• Depletion of ligand indicates binding

👉 Also reveals:

• Size changes upon binding

📄 Page 20 — Fluorescence

Figure shows:

• Tryptophan emission shifts

Key concept:

• Environment changes fluorescence:
  • buried → different signal
  • exposed → different signal

👉 Binding → structural change → signal change

📄 Page 21 — NMR

Figure: HSQC shifts

👉 Concept:

• Each peak = residue
• Binding → chemical shift changes

🧠 Powerful because:

• Gives residue-level information

📄 Page 22 — Circular Dichroism (CD)

Figure shows:

• α-helix, β-sheet, random coil signatures

👉 Binding can:

• change structure → change CD signal

📄 Page 23–24 — CD setup

Images show:

• optical system with polarized light

👉 Key principle:

• Measures difference in absorption of left vs right polarized light

📄 Page 25 — Solid-phase assays

Figure:

• Binding vs ligand concentration

👉 KD is:

• 50% binding point

📄 Page 26 — ITC basics

Reaction: M + L leftrightarrow ML

👉 Measures:

• Heat released or absorbed

🧠 Important:

• Direct thermodynamic method

📄 Page 27 — ITC principle

Figure explanation:

• Instrument keeps temperature constant
• Measures energy needed

👉 If heat absorbed:

• endothermic

📄 Page 29 — ITC data

Figure shows:

• Peaks (each injection)
• Integrated curve → binding isotherm

👉 From this you get:

• KD
• ΔH
• stoichiometry

📄 Page 30 — ITC vs other methods

ITC gives:

• ΔH directly
• KD → ΔG
• ΔS (via equation)

Other methods:

• Mostly give KD only

👉 ITC = complete thermodynamics

📄 Page 31–34 — SPR (Surface Plasmon Resonance)

Concept:

• Light excites electrons at surface
• Binding changes refractive index

👉 Measured as:

• shift in resonance angle

📄 Page 35 — SPR advantages

• Real-time
• Label-free
• Gives kinetics:
  • kon
  • koff

📄 Page 36 — SPR pitfalls

• Surface effects
• Non-specific binding
• Experimental setup critical

📄 Page 37 — SPR visualization

Image:

• ligand immobilized on surface
• analyte flows over

📄 Page 38–40 — BLI (Biolayer Interferometry)

Principle:

• Light interference changes when thickness changes

👉 Binding → thicker layer → signal shift

📄 Page 42 — BLI biosensors

Different sensors:

• antibodies
• His-tags
• biotin

👉 Tailored for different experiments

📄 Page 43 — What BLI gives

• KD
• kon / koff
• concentration
• epitope mapping

📄 Page 45 — Summary of methods

📄 Page 46 — Exercises

• Practice applying all concepts

🧠 Final Big Picture

This lecture teaches:

1. How binding works

• KD determines affinity
• Cooperativity shapes response

2. How to model it

• Quadratic equations when concentrations matter
• Microscopic vs macroscopic KD

3. How to measure it

• Structural methods (NMR, CD)
• Thermodynamic (ITC)
• Kinetic (SPR, BLI)

🔥 Key conceptual takeaways

• KD is not just a number → it defines biological function
• You must distinguish:
  • free vs total ligand
• Cooperativity turns binding into a switch-like system
• Different methods give different layers of information